Applied AI Engineer

Job Title

Applied AI Engineer

Role Summary

Join NVIDIA's Silicon Co-Design Group to design, build, and deploy AI-driven solutions that improve chip design, validation, and automation workflows. The role focuses on architecting scalable AI systems and integrating them across engineering teams to accelerate silicon development.

Experience Level

Mid-level role. Candidates should have approximately 5+ years of experience building and deploying ML/AI systems or data-intensive backend services and 2+ years directly owning applied AI or LLM-powered workflows end-to-end.

Responsibilities

Deliver production AI systems that remove friction across silicon development and validation pipelines.

• Design and deploy LLM-powered validation and automation pipelines for post-silicon and semiconductor environments.
• Integrate AI solutions with cross-functional engineering teams and operational workflows.
• Evaluate emerging AI frameworks and architectures and recommend adoption strategies.
• Build monitoring, measurement, and data systems to quantify AI impact and drive continuous improvement.
• Lead projects from prototype to production deployment, including scalable model deployment, monitoring, and debugging.

Requirements

Must-have technical skills and domain experience.

• 5+ years hands-on experience building and deploying ML/AI systems or data-intensive backend services.
• 2+ years directly owning an applied AI agent, LLM-powered workflow, or intelligent automation system end-to-end.
• Strong Python skills and proficiency in at least one compiled/static language (C, C++, C#, Java, or Scala).
• Proven experience deploying, monitoring, and debugging scalable AI/ML models in production.
• Solid electrical engineering fundamentals: computer architecture, high-speed interfaces, timing, power basics, and familiarity with firmware/driver interactions.
• Experience in silicon development environments and chip/system characterization methodologies.
• Hands-on lab experience with silicon bring-up, characterization, or debug tools (oscilloscopes, multimeters, logic analyzers).
• Strong problem-solving, communication, and ability to manage multiple projects concurrently.

Nice-to-have:

• Experience with deep learning frameworks (PyTorch, TensorFlow) and agent/orchestration tooling (NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, n8n).
• Proven record debugging complex HW/SW system-level interactions and driving root-cause analysis.

Education Requirements

Bachelor's, Master's, or PhD (BS/MS/PhD) in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field — or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.